code: def __init__(self, vocab_size, embed_size, hidden_size, num_layers):
      super(RNNLM, self).__init__()
      self.embed = nn.Embedding(vocab_size, embed_size)
      self.lstm = nn.LSTM(
          embed_size, hidden_size, num_layers, batch_first=True
      )
      self.linear = nn.Linear(hidden_size, vocab_size)
  
file_path: pytorch-tutorial/tutorials/02-intermediate/language_model/main.py
imports: import torch
  import torch.nn
  import numpy
  from torch.nn.utils import clip_grad_norm_
  from data_utils import Dictionary, Corpus
label_desc: Use image node_id 1 to create a new RNNLM object from inherited base classes: nn with example: obj = RNNLM(vocab_size, embed_size, hidden_size, num_layers)